In this work, a novel approach to scientific visualization and steerable texture synthesis is presented. Vector field visualization and synthesis techniques for controlled, field-driven texture generation are proposed, discussed, and extended to allow more control and degrees of freedom in the image creation. Concepts from perception and cognition, as well as statistical theory for standard texture synthesis, were investigated and used to motivate and improve the proposed techniques. The approach results to be general, flexible, and open to further extensions and integrations. Vector fields can be visualized in a straightforward manner by setting the color of output pixels on the base of computed similarity functions. The proposed method is texture-based and it locally adapts and transforms a chosen basic pattern of an anisotropic texture to represent the features and the variation of the field. In general, it allows any procedural or manual way to define a mapping from vector space to example image space, offering arbitrary degrees of freedom in representing the appearance of the resulting field. The approach to visualization of vectorial data sets can be interpreted as an hybrid algorithm, which combines features of direct intuitive visualization, such as simplicity, intuitivity, generality, together with features from dense visualization techniques, such as powerful information encoding, locality of calculation, accuracy. The variety of tasks and the different level of expertise and experience of users motivate and strongly require such versatility. The steerable generation of non-homogeneous textures offers several degrees of freedom in the synthesis process, allowing a variety of effects for appealing output images. Textural elements used as primitive provide for this task a numerous set of visual dimensions for arbitrary variation. In general, the proposed techniques bring together concepts from human vision and perception, statistics and texture synthesis, and visualization, in an interesting interdisciplinary research that promises encouraging results for several fields of applications.